Engine wear and used oil analysis - comparative study in high speed diesel engines

The operational life and reliability of I.C. engines are limited to a certain extent by the break down of the engine components due to wear. It is advantageous to know the condition of an engine and its components without disassembling for detailed measurements. This paper describes the possibility of employing chemical analysis of the used crank case oil to predict the wear of engine components. It is concluded that the acidity and carbon contents of the crank case oil play a significant role in assessing the wear of copper-lead bearings used for the big end of the connecting rod.

Engine wear and used oil analysis-A comparative study in high speed diesel engines

The operational life and reliability of I.C. engines are limited to a certain extent by the break down of the engine components due to wear. It is advantageous to know the condition of an engine and its components without disassembling for detailed measurements. This paper describes the possibility of employing chemical analysis of the used crank case oil to predict the wear of engine components. It is concluded that the acidity and carbon contents of the crank case oil play a significant role in assessing the wear of copper-lead bearings used for the big end of the connecting rod.

Vibration and oil analysis for monitoring problems related to water contamination in rolling

Trying to reduce particle contamination in lubrication systems, industries of the whole world spend millions of dollars each year on the improvement of filtration technology. In this context, by controlling fluid cleanliness, some companies are able to reduce failures rates up to 85 percent. However, in some industries and environments, water is a contaminant more frequently encountered than solid particles, and it is often seen as the primary cause of component failure. Only one percent of water in oil is enough to reduce life expectancy of a journal bearing by 80 percent. For rolling bearing elements, the situation is worse because water destroys the oil film and, under the extreme temperatures and pressures generated in the load zone of a rolling bearing element, free and emulsified water can result in instantaneous flash-vaporization giving origin to erosive wear. This work studies the effect of water as lubricant contaminant in ball bearings, which simulates a situation that could actually occur in real systems. In a designed bench test, three basic lubricants of different viscosities were contaminated with different contents of water. The results regarding oil and vibration analysis are presented for different bearing speeds.

Maintenance of a reducer by vibration and wear particles analysis

Purpose - The purpose of the paper is to provide information on wear debris on oil and vibration analysis as predictive maintenance techniques in reducer. Design/methodology/approach - The estate of a reducer is verified by analyzing the vibration and oil conditions of a test rig under well-designed conditions utilizing some predictive variables. Findings - According to the vibration and oil analysis it is found out what it was happening into the reducer without disassembling it. Practical implications - This paper demonstrates the use of oil debris analysis and vibration analysis as a technique that enhances preventive maintenance practices. The paper helps practitioners to utilize these techniques more effectively. Originality/value - This paper gives information about two predictive maintenance techniques with a test rig. © Emerald Group Publishing Limited.

Vibration and wear particles analysis in a test stand

Purpose - This paper aims to provide information on wear debris on oil and vibration analysis as predictive maintenance techniques. Design/methodology/ approach - The estate of a reducer is verified by analyzing the vibration and oil conditions of a test rig under some variables. Findings - According to the vibration and oil analysis it was found what was happening in the reducer without disassembling it. Originality/value - This paper gives information about two predictive maintenance techniques with a test rig. © Emerald Group Publishing Limited.

Dietary fish oil replacement with lard and soybean oil affects triacylglycerol and phospholipid muscle and liver docosahexaenoic acid content but not in the brain and eyes of surubim juveniles Pseudoplatystoma sp

Triplicate groups of juvenile suribim were fed for 183 days one of four different isonitrogenous (47.6% crude protein) and isolipidic (18.7% lipid) diets formulated using three different lipid sources: 100% fish oil (FO, diet 1); 100% pig lard (L, diet 2); 100% soybean oil (SO, diet 3), and FO/L/SO (1:1:1, w/w/w; diet 4). The tissue levels of fatty acids 18:2n - 6 and 18:3n - 3 decreased relative to corresponding dietary fatty acid values. The 20:5n - 3 and 22:6n - 3 composition of muscle and liver neutral lipids were linearly correlated with corresponding dietary fatty acid composition. In contrast, the 22:6n - 3 composition of the brain and eye were similar among treatments. The 22:6n - 3 level was enriched in all tissues, particularly in the neural tissues. Similar results were observed for tissue polar lipids: fatty acids content reflected dietary composition, with the exception of the 22:6n - 3 level, which showed enrichment and no differences between groups. Given these results, the importance of the biochemical functions (transport and/or metabolism) of 22:6n - 3 in the development of the neural system of surubim warrants further investigation. © Springer Science+Business Media B.V. 2008.

Catalytic pyrolysis of agricultural residues for bio-oil production

Agricultural residues from Thailand, namely stalk and rhizome of cassava plants, were employed as raw materials for bio-oil production via fast pyrolysis technology. There were two main objectives of this project. The first one was to determine the optimum pyrolysis temperature for maximising the organics yield and to investigate the properties of the bio-oils produced. To achieve this objective, pyrolysis experiments were conducted using a bench-scale (150 g/h) reactor system, followed by bio-oil analysis. It was found that the reactor bed temperature that could give the highest organics yield for both materials was 490±15ºC. At all temperatures studied, the rhizome gave about 2-4% higher organics yields than the stalk. The bio-oil derived from the rhizome had lower oxygen content, higher calorific value and better stability, thus indicating better quality than that produced from the stalk. The second objective was to improve the bio-oil properties in terms of heating value, viscosity and storage stability by the incorporation of catalyst into the pyrolysis process. Catalytic pyrolysis was initially performed in a micro-scale reactor to screen a large number of catalysts. Subsequently, seven catalysts were selected for experiments with larger-scale (150 g/h) pyrolysis unit. The catalysts were zeolite and related materials (ZSM-5, Al-MCM-41 and Al-MSU-F), commercial catalysts (Criterion-534 and MI-575), copper chromite and ash. Additionally, the combination of two catalysts in series was investigated. These were Criterion-534/ZSM-5 and Al-MSU-F/ZSM-5. The results showed that all catalysts could improve the bio-oils properties as they enhanced cracking and deoxygenation reactions and in some cases such as ZSM-5, Criterion-534 and Criterion-534/ZSM-5, valuable chemicals like hydrocarbons and light phenols were produced. The highest concentration of these compounds was obtained with Criterion-534/ZSM-5.

Latent degradation indicators estimation and prediction : a Monte Carlo approach

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

孤岛油田曲流河微相单砂体储层建筑结构及挖潜方向研究

In the intermediary and later stage of oil field development, remaining oil disperses fiercely, the contradiction in the layer has become the main problem and the distribution of remaining oil is transforming to the difference of single sand-body. So, the fine description research of reservoir is becoming a tendency and the methods of remaining oil research need new developments. In the research of “The Single-sand-body Architectural Element and Potentiality Analysis Research of Meandering River, GuDao Oil Field”, the research principle is analytical hierarchy process and schema prescription what are reservoir fine description methods under the condition of dense well pattern. The knowledge of regional sedimentary system and sedimentary facies is the foundation of this research. According to the 3D distribution model of the microfacies sand-body of fluvial facies, stratigraphic unit classification & coenocorrelation of 154 wells are completed in the research of meandering river sand-body in Ng3-4. In this research, the 3D distribution of microfacies sand-body in the main layers are settled. The architectural element model of Ng4 point bar is analysed using the drill core and FMI data. According to the overgrow model of point bar, the surfaces of lateral accretion is traced and the architectural element model of point bar is settled. In the research, the control of micro-facies sand-body of meandering river to the distribution of remaining oil is analysed and the potential area is proposed. All these will play an important role in the development of GuDao oil field. In this research, abundant of logging data, drill core data and production performance data are used to analyse the contributing factor of single sand-body in the Ng3-4 meandering river. Using the technology of geological modeling, all that are researched including the 3D distribution scales of meandering river point bar, the control affection of inner lateral accretion layer to the distribution of oil & gas and remaining. Then, the way of remaining oil development in the sand-body of meandering river is improved. The innovation of the research technology includes (1) the presentation of the conception and research methods of micro-facies sand-body (2) enriching the content of reservoir architectural element research and (3) to renew the research method of remaining oil analysis. The research has practiced with obvious effect.(1)It is deepened into understand the river facies reservoir construction of Gudao oil field, By Building the reservoir construction and studying the effect of diffent deposit or geological interface to fluid partition and to the distribution of the remaining oil, we improved the understanding to the distribution of the remaining oil；(2)By building the distribution mod of the remaining oil in the reservoir construction and making the remaining oil description detailed,the development direction of old oil field is more clear；(3)Expanded the application scales of the horizontal well and enhanced the application effects of the horizontal well technique , we designed and drilled 23 ports horizontal wells in all , the cumulative hydrocarbon production is 10.6*104 t；(4) According to the findings of the internal building structure in reservoir of the fluvial facies in the region of interest, and uniting the injection/production corresponding states、the producing history and the dynamic monitoring documents of the oil/water wells in the flooding units , we researched the residual oil distribution in the point bar , and found the distribution regular patterns of the remaining oil, and comprehended the distribution of the remaining oil . In base of that , we proceeded the optimizing designs of the oil well potentialities , and advanced the effect of the treatment potentials . It is proved that , it was very important that internal building structure research of the single sand body of reservoir for guiding the high efficiency potentialities of the remaining oil in the high water cut stage .

Previsão de avarias em transformadores de potência através da análise de ensaios físico-químicos

Os Transformadores de potência são máquinas de elevada importância ao nível dos Sistemas Elétricos de Energia (SEE) uma vez que são estas máquinas que possibilitam a interligação dos diferentes níveis de tensão da rede e a transmissão de energia elétrica em Corrente Alternada (CA). Geralmente, estas máquinas são de grandes dimensões e de elevado nível de complexidade construtiva. Caracterizam-se por possuírem períodos de vida útil bastante elevados (vinte a trinta anos) e preços elevados, o que conduz a um nível de exigência de fiabilidade muito elevada, uma vez que não e viável a existência de muitos equipamentos de reserva nos SEE. Com o objetivo de tentar maximizar o período de vida útil dos transformadores de potência e a sua fiabilidade, tenta-se, cada vez mais, implementar conceitos de manutenção preventiva a este tipo de máquinas. No entanto, a gestão da sua vida útil e extremamente complexa na medida em que, estas máquinas têm vários componentes cruciais e suscetiveis de originar falhas e, quase todos eles, encontram-se no interior de uma cuba. Desta forma, não e possível obter uma imagem do seu estado, em tempo real, sem colocar o transformador fora de serviço, algo que acarreta custos elevados. Por este motivo, desenvolveu-se uma técnica que permite obter uma indicação do estado do transformador, em tempo real, sem o retirar de serviço, colhendo amostras do óleo isolante e procedendo a sua análise físico-química e Analise Gases Dissolvidos (DGA). As análises aos óleos isolantes tem vindo a adquirir uma preponderância muito elevada no diagnóstico de falhas e na analise do estado de conservação destes equipamentos tendo-se desenvolvido regras para interpretação dos parâmetros dos óleos com carácter normativo. Considerando o conhecimento relativo a interpretação dos ensaios físico-químicos e DGA ao oleol, e possível desenvolver ferramentas capazes de otimizar essas mesmas interpretações e aplicar esse conhecimento no sentido de prever a sua evolução, assim como o surgimento de possíveis falhas em transformadores, para assim otimizar os processos de manutenção. Neste campo as Redes Neuronais Artificiais (RNAs) têm um papel fundamental

Concentrations of free amino acids and sugars in nine potato varieties: effects of storage and relationship with acrylamide formation

Acrylamide forms during cooking and processing predominately from the reaction of free asparagine and reducing sugars in the Maillard reaction. The identification of low free asparagine and reducing sugar varieties of crops is therefore an important target. In this study, nine varieties of potato (French fry varieties Maris Piper (from two suppliers), Pentland Dell, King Edward, Daisy, and Markies; and chipping varieties Lady Claire, Lady Rosetta, Saturna, and Hermes) grown in the United Kingdom in 2009 were analyzed at monthly intervals through storage from November 2009 to July 2010. Acrylamide formation was measured in heated flour and chips fried in oil. Analysis of variance revealed significant interactions between varieties nested within type (French fry and chipping) and storage time for most free amino acids, glucose, fructose, and acrylamide formation. Acrylamide formed in chips correlated significantly with acrylamide formed in flour and with chip color. There were significant correlations between glucose or total reducing sugar concentration and acrylamide formation in both variety types, but with fructose the correlation was much stronger for chipping than for French fry varieties. Conversely, there were significant correlations with acrylamide formation for both total free amino acid and free asparagine concentration in the French fry but not chipping varieties. The study showed the potential of variety selection for preventing unacceptable levels of acrylamide formation in potato products and the variety-dependent effect of long-term storage on acrylamide risk. It also highlighted the complex relationship between precursor concentration and acrylamide risk in potatoes.

Níveis de potássio em solução nutritiva, desenvolvimento de plantas e a produção de óleo essencial de mentha piperita L

Pós-graduação em Agronomia (Horticultura) - FCA

Procedimentos de coletas de óleo para análise preditiva de turbinas à gás

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)